Overview

Brought to you by YData

Dataset statistics

Number of variables14
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.1 KiB
Average record size in memory113.3 B

Variable types

Text13
Categorical1

Alerts

Country has unique values Unique

Reproduction

Analysis started2025-01-27 10:12:22.876340
Analysis finished2025-01-27 10:12:24.432712
Duration1.56 second
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

Country
Text

Unique 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:24.826488image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length7.81
Min length4

Characters and Unicode

Total characters781
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowUnited States
2nd rowChina
3rd rowGermany
4th rowJapan
5th rowIndia
ValueCountFrequency (%)
united 3
 
2.6%
republic 2
 
1.7%
south 2
 
1.7%
spain 1
 
0.9%
japan 1
 
0.9%
india 1
 
0.9%
kingdom 1
 
0.9%
france 1
 
0.9%
italy 1
 
0.9%
canada 1
 
0.9%
Other values (102) 102
87.9%
2025-01-27T15:42:25.622331image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 124
15.9%
i 65
 
8.3%
n 62
 
7.9%
e 52
 
6.7%
r 47
 
6.0%
o 38
 
4.9%
t 31
 
4.0%
u 30
 
3.8%
l 29
 
3.7%
d 21
 
2.7%
Other values (40) 282
36.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 781
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 124
15.9%
i 65
 
8.3%
n 62
 
7.9%
e 52
 
6.7%
r 47
 
6.0%
o 38
 
4.9%
t 31
 
4.0%
u 30
 
3.8%
l 29
 
3.7%
d 21
 
2.7%
Other values (40) 282
36.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 781
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 124
15.9%
i 65
 
8.3%
n 62
 
7.9%
e 52
 
6.7%
r 47
 
6.0%
o 38
 
4.9%
t 31
 
4.0%
u 30
 
3.8%
l 29
 
3.7%
d 21
 
2.7%
Other values (40) 282
36.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 781
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 124
15.9%
i 65
 
8.3%
n 62
 
7.9%
e 52
 
6.7%
r 47
 
6.0%
o 38
 
4.9%
t 31
 
4.0%
u 30
 
3.8%
l 29
 
3.7%
d 21
 
2.7%
Other values (40) 282
36.1%
Distinct87
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:26.166250image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length7.97
Min length3

Characters and Unicode

Total characters797
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)77.0%

Sample

1st rowApple Pay
2nd rowAlipay
3rd rowPayPal
4th rowPayPay
5th rowPhonePe
ValueCountFrequency (%)
pay 11
 
7.8%
money 10
 
7.1%
mobile 4
 
2.8%
apple 3
 
2.1%
mobilepay 3
 
2.1%
orange 3
 
2.1%
cash 3
 
2.1%
paypal 2
 
1.4%
line 2
 
1.4%
tigo 2
 
1.4%
Other values (92) 98
69.5%
2025-01-27T15:42:27.042105image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 99
 
12.4%
e 57
 
7.2%
y 50
 
6.3%
i 44
 
5.5%
P 43
 
5.4%
41
 
5.1%
o 41
 
5.1%
n 41
 
5.1%
M 34
 
4.3%
l 30
 
3.8%
Other values (45) 317
39.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 797
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 99
 
12.4%
e 57
 
7.2%
y 50
 
6.3%
i 44
 
5.5%
P 43
 
5.4%
41
 
5.1%
o 41
 
5.1%
n 41
 
5.1%
M 34
 
4.3%
l 30
 
3.8%
Other values (45) 317
39.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 797
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 99
 
12.4%
e 57
 
7.2%
y 50
 
6.3%
i 44
 
5.5%
P 43
 
5.4%
41
 
5.1%
o 41
 
5.1%
n 41
 
5.1%
M 34
 
4.3%
l 30
 
3.8%
Other values (45) 317
39.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 797
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 99
 
12.4%
e 57
 
7.2%
y 50
 
6.3%
i 44
 
5.5%
P 43
 
5.4%
41
 
5.1%
o 41
 
5.1%
n 41
 
5.1%
M 34
 
4.3%
l 30
 
3.8%
Other values (45) 317
39.8%

Market Share
Categorical

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
15%
21 
20%
17 
10%
11 
25%
11 
30%
10 
Other values (20)
30 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters300
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)15.0%

Sample

1st row43%
2nd row55%
3rd row32%
4th row31%
5th row47%

Common Values

ValueCountFrequency (%)
15% 21
21.0%
20% 17
17.0%
10% 11
11.0%
25% 11
11.0%
30% 10
10.0%
35% 4
 
4.0%
40% 4
 
4.0%
22% 3
 
3.0%
50% 2
 
2.0%
43% 2
 
2.0%
Other values (15) 15
15.0%

Length

2025-01-27T15:42:27.364870image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
15 21
21.0%
20 17
17.0%
10 11
11.0%
25 11
11.0%
30 10
10.0%
35 4
 
4.0%
40 4
 
4.0%
22 3
 
3.0%
43 2
 
2.0%
50 2
 
2.0%
Other values (15) 15
15.0%

Most occurring characters

ValueCountFrequency (%)
% 100
33.3%
0 45
15.0%
5 42
14.0%
2 40
 
13.3%
1 34
 
11.3%
3 21
 
7.0%
4 13
 
4.3%
7 2
 
0.7%
9 1
 
0.3%
6 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 300
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
% 100
33.3%
0 45
15.0%
5 42
14.0%
2 40
 
13.3%
1 34
 
11.3%
3 21
 
7.0%
4 13
 
4.3%
7 2
 
0.7%
9 1
 
0.3%
6 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 300
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
% 100
33.3%
0 45
15.0%
5 42
14.0%
2 40
 
13.3%
1 34
 
11.3%
3 21
 
7.0%
4 13
 
4.3%
7 2
 
0.7%
9 1
 
0.3%
6 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 300
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
% 100
33.3%
0 45
15.0%
5 42
14.0%
2 40
 
13.3%
1 34
 
11.3%
3 21
 
7.0%
4 13
 
4.3%
7 2
 
0.7%
9 1
 
0.3%
6 1
 
0.3%
Distinct86
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:27.841074image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length68
Median length32
Mean length12.63
Min length6

Characters and Unicode

Total characters1263
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)77.0%

Sample

1st rowapple.com/apple-pay
2nd rowalipay.com
3rd rowpaypal.com
4th rowpaypay.ne.jp
5th rowphonepe.com
ValueCountFrequency (%)
mobilepay.dk 4
 
4.0%
orange.com 3
 
3.0%
mpesa.com 3
 
3.0%
apple.com/apple-pay 3
 
3.0%
momo.mtn.com 2
 
2.0%
paypal.com 2
 
2.0%
alipay.com 2
 
2.0%
gcash.com 2
 
2.0%
zaincash.iq 2
 
2.0%
yoomoney.ru 1
 
1.0%
Other values (77) 77
76.2%
2025-01-27T15:42:28.614579image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 133
 
10.5%
a 124
 
9.8%
. 119
 
9.4%
m 103
 
8.2%
c 94
 
7.4%
p 76
 
6.0%
e 72
 
5.7%
i 52
 
4.1%
n 52
 
4.1%
s 48
 
3.8%
Other values (25) 390
30.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1263
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 133
 
10.5%
a 124
 
9.8%
. 119
 
9.4%
m 103
 
8.2%
c 94
 
7.4%
p 76
 
6.0%
e 72
 
5.7%
i 52
 
4.1%
n 52
 
4.1%
s 48
 
3.8%
Other values (25) 390
30.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1263
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 133
 
10.5%
a 124
 
9.8%
. 119
 
9.4%
m 103
 
8.2%
c 94
 
7.4%
p 76
 
6.0%
e 72
 
5.7%
i 52
 
4.1%
n 52
 
4.1%
s 48
 
3.8%
Other values (25) 390
30.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1263
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 133
 
10.5%
a 124
 
9.8%
. 119
 
9.4%
m 103
 
8.2%
c 94
 
7.4%
p 76
 
6.0%
e 72
 
5.7%
i 52
 
4.1%
n 52
 
4.1%
s 48
 
3.8%
Other values (25) 390
30.9%
Distinct85
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:29.020846image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length134
Median length90
Mean length55.83
Min length35

Characters and Unicode

Total characters5583
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)74.0%

Sample

1st rowhttps://www.pcmag.com/reviews/apple-pay
2nd rowhttps://www.rapyd.net/blog/what-is-alipay/
3rd rowhttps://www.cnet.com/reviews/paypal-review/
4th rowhttps://www.g2.com/products/paypay/reviews
5th rowhttps://www.trustpilot.com/review/phonepe.com
ValueCountFrequency (%)
https://www.pcmag.com/reviews/apple-pay 3
 
2.8%
https://tech-ish.com/2021/02/01/new-m-pesa-app-really-good 3
 
2.8%
https://ca.trustpilot.com/review/mobilepay.dk 3
 
2.8%
https://africanreview.com/finance/banking-a-finance/orange-money-fintech-is-proving-a-game-changer-in-africa 3
 
2.8%
https://www.rapyd.net/blog/what-is-alipay 2
 
1.9%
https://www.appbrain.com/app/zaincash-%d8%b2%d9%8a%d9%86-%d9%83%d8%a7%d8%b4/mobi.foo.zaincash 2
 
1.9%
https://ca.trustpilot.com/review/www.gcash.com 2
 
1.9%
https://www.cnet.com/reviews/paypal-review 2
 
1.9%
https://tigo-money-bolivia.en.softonic.com/android 2
 
1.9%
https://www.g2.com/products/paypay/reviews 2
 
1.9%
Other values (81) 83
77.6%
2025-01-27T15:42:29.948087image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 455
 
8.1%
t 453
 
8.1%
o 340
 
6.1%
e 337
 
6.0%
p 335
 
6.0%
a 328
 
5.9%
i 278
 
5.0%
s 274
 
4.9%
. 257
 
4.6%
c 245
 
4.4%
Other values (54) 2281
40.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5583
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 455
 
8.1%
t 453
 
8.1%
o 340
 
6.1%
e 337
 
6.0%
p 335
 
6.0%
a 328
 
5.9%
i 278
 
5.0%
s 274
 
4.9%
. 257
 
4.6%
c 245
 
4.4%
Other values (54) 2281
40.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5583
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 455
 
8.1%
t 453
 
8.1%
o 340
 
6.1%
e 337
 
6.0%
p 335
 
6.0%
a 328
 
5.9%
i 278
 
5.0%
s 274
 
4.9%
. 257
 
4.6%
c 245
 
4.4%
Other values (54) 2281
40.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5583
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 455
 
8.1%
t 453
 
8.1%
o 340
 
6.1%
e 337
 
6.0%
p 335
 
6.0%
a 328
 
5.9%
i 278
 
5.0%
s 274
 
4.9%
. 257
 
4.6%
c 245
 
4.4%
Other values (54) 2281
40.9%
Distinct87
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:30.443841image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2200
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)79.0%

Sample

1st rowhttps://ibb.co/gTyz7dQ
2nd rowhttps://ibb.co/ysHqJN4
3rd rowhttps://ibb.co/JxbrsQ1
4th rowhttps://ibb.co/v1Xgpvs
5th rowhttps://ibb.co/YfdMZjP
ValueCountFrequency (%)
https://ibb.co/hc51xx8 4
 
3.8%
https://ibb.co/85zhxb9 3
 
2.9%
https://ibb.co/0mptpcg 3
 
2.9%
https://ibb.co/gtyz7dq 3
 
2.9%
accessable 2
 
1.9%
https://ibb.co/jxbrsq1 2
 
1.9%
https://ibb.co/yshqjn4 2
 
1.9%
not 2
 
1.9%
website 2
 
1.9%
https://ibb.co/xc141gy 2
 
1.9%
Other values (79) 79
76.0%
2025-01-27T15:42:31.295299image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 294
13.4%
t 212
 
9.6%
b 206
 
9.4%
c 117
 
5.3%
s 117
 
5.3%
h 111
 
5.0%
p 111
 
5.0%
i 100
 
4.5%
o 100
 
4.5%
. 98
 
4.5%
Other values (51) 734
33.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2200
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 294
13.4%
t 212
 
9.6%
b 206
 
9.4%
c 117
 
5.3%
s 117
 
5.3%
h 111
 
5.0%
p 111
 
5.0%
i 100
 
4.5%
o 100
 
4.5%
. 98
 
4.5%
Other values (51) 734
33.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2200
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 294
13.4%
t 212
 
9.6%
b 206
 
9.4%
c 117
 
5.3%
s 117
 
5.3%
h 111
 
5.0%
p 111
 
5.0%
i 100
 
4.5%
o 100
 
4.5%
. 98
 
4.5%
Other values (51) 734
33.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2200
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 294
13.4%
t 212
 
9.6%
b 206
 
9.4%
c 117
 
5.3%
s 117
 
5.3%
h 111
 
5.0%
p 111
 
5.0%
i 100
 
4.5%
o 100
 
4.5%
. 98
 
4.5%
Other values (51) 734
33.4%
Distinct68
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:31.804971image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.03
Min length3

Characters and Unicode

Total characters803
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)59.0%

Sample

1st rowGoogle Pay
2nd rowWeChat Pay
3rd rowKlarna
4th rowLINE Pay
5th rowGoogle Pay
ValueCountFrequency (%)
paypal 24
 
17.5%
pay 13
 
9.5%
apple 4
 
2.9%
mobile 4
 
2.9%
money 3
 
2.2%
samsung 2
 
1.5%
klarna 2
 
1.5%
wechat 2
 
1.5%
google 2
 
1.5%
banca 2
 
1.5%
Other values (75) 79
57.7%
2025-01-27T15:42:32.716363image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 134
16.7%
P 79
 
9.8%
y 63
 
7.8%
l 59
 
7.3%
e 50
 
6.2%
37
 
4.6%
o 37
 
4.6%
n 30
 
3.7%
i 27
 
3.4%
r 20
 
2.5%
Other values (46) 267
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 803
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 134
16.7%
P 79
 
9.8%
y 63
 
7.8%
l 59
 
7.3%
e 50
 
6.2%
37
 
4.6%
o 37
 
4.6%
n 30
 
3.7%
i 27
 
3.4%
r 20
 
2.5%
Other values (46) 267
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 803
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 134
16.7%
P 79
 
9.8%
y 63
 
7.8%
l 59
 
7.3%
e 50
 
6.2%
37
 
4.6%
o 37
 
4.6%
n 30
 
3.7%
i 27
 
3.4%
r 20
 
2.5%
Other values (46) 267
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 803
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 134
16.7%
P 79
 
9.8%
y 63
 
7.8%
l 59
 
7.3%
e 50
 
6.2%
37
 
4.6%
o 37
 
4.6%
n 30
 
3.7%
i 27
 
3.4%
r 20
 
2.5%
Other values (46) 267
33.3%
Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:33.341444image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length35
Median length26
Mean length12.23
Min length6

Characters and Unicode

Total characters1223
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)58.0%

Sample

1st rowpay.google.com
2nd rowweixin.qq.com
3rd rowklarna.com
4th rowpay.line.me
5th rowpay.google.com
ValueCountFrequency (%)
paypal.com 24
24.0%
apple.com/apple-pay 4
 
4.0%
mercadopago.com 2
 
2.0%
revolut.com 2
 
2.0%
samsung.com/samsung-pay 2
 
2.0%
pay.google.com 2
 
2.0%
weixin.qq.com 2
 
2.0%
klarna.com 2
 
2.0%
momo.mtn.com 2
 
2.0%
gopay.co.id 1
 
1.0%
Other values (57) 57
57.0%
2025-01-27T15:42:34.131225image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 155
12.7%
o 125
10.2%
. 120
9.8%
p 110
 
9.0%
c 106
 
8.7%
m 105
 
8.6%
l 61
 
5.0%
y 56
 
4.6%
e 54
 
4.4%
n 48
 
3.9%
Other values (19) 283
23.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1223
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 155
12.7%
o 125
10.2%
. 120
9.8%
p 110
 
9.0%
c 106
 
8.7%
m 105
 
8.6%
l 61
 
5.0%
y 56
 
4.6%
e 54
 
4.4%
n 48
 
3.9%
Other values (19) 283
23.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1223
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 155
12.7%
o 125
10.2%
. 120
9.8%
p 110
 
9.0%
c 106
 
8.7%
m 105
 
8.6%
l 61
 
5.0%
y 56
 
4.6%
e 54
 
4.4%
n 48
 
3.9%
Other values (19) 283
23.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1223
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 155
12.7%
o 125
10.2%
. 120
9.8%
p 110
 
9.0%
c 106
 
8.7%
m 105
 
8.6%
l 61
 
5.0%
y 56
 
4.6%
e 54
 
4.4%
n 48
 
3.9%
Other values (19) 283
23.1%
Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:34.581122image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length131
Median length92
Mean length52.42
Min length33

Characters and Unicode

Total characters5242
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)58.0%

Sample

1st rowhttps://www.pcmag.com/reviews/google-pay
2nd rowhttps://www.weareplanet.com/blog/wechat-pay
3rd rowhttps://www.trustpilot.com/review/klarna.com
4th rowhttps://www.trustpilot.com/review/linepay.fun
5th rowhttps://www.pcmag.com/reviews/google-pay
ValueCountFrequency (%)
https://www.cnet.com/reviews/paypal-review 24
 
22.2%
https://www.pcmag.com/reviews/apple-pay 4
 
3.7%
https://www.capterra.com/p/250909/mercado-pago/reviews 2
 
1.9%
https://pctechmag.com/2020/05/mtn-momo-app-review 2
 
1.9%
https://www.trustpilot.com/review/www.revolut.com 2
 
1.9%
https://www.capterra.in/reviews/213917/samsung-pay#:~:text=the%20interface%20is%20good%2c%20simple,a%20great%20option%20to%20value 2
 
1.9%
https://www.pcmag.com/reviews/google-pay 2
 
1.9%
https://www.weareplanet.com/blog/wechat-pay 2
 
1.9%
https://www.trustpilot.com/review/klarna.com 2
 
1.9%
https://www.trustpilot.com/review/www.nexi.it 1
 
0.9%
Other values (65) 65
60.2%
2025-01-27T15:42:35.288342image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 468
 
8.9%
p 381
 
7.3%
t 378
 
7.2%
e 371
 
7.1%
a 294
 
5.6%
w 292
 
5.6%
o 266
 
5.1%
s 257
 
4.9%
. 238
 
4.5%
i 234
 
4.5%
Other values (56) 2063
39.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5242
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 468
 
8.9%
p 381
 
7.3%
t 378
 
7.2%
e 371
 
7.1%
a 294
 
5.6%
w 292
 
5.6%
o 266
 
5.1%
s 257
 
4.9%
. 238
 
4.5%
i 234
 
4.5%
Other values (56) 2063
39.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5242
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 468
 
8.9%
p 381
 
7.3%
t 378
 
7.2%
e 371
 
7.1%
a 294
 
5.6%
w 292
 
5.6%
o 266
 
5.1%
s 257
 
4.9%
. 238
 
4.5%
i 234
 
4.5%
Other values (56) 2063
39.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5242
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 468
 
8.9%
p 381
 
7.3%
t 378
 
7.2%
e 371
 
7.1%
a 294
 
5.6%
w 292
 
5.6%
o 266
 
5.1%
s 257
 
4.9%
. 238
 
4.5%
i 234
 
4.5%
Other values (56) 2063
39.4%
Distinct68
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:35.793959image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2200
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)60.0%

Sample

1st rowhttps://ibb.co/bK79xby
2nd rowhttps://ibb.co/Qk6Z7mw
3rd rowhttps://ibb.co/0F1XnJ8
4th rowhttps://ibb.co/hW2py4P
5th rowhttps://ibb.co/bK79xby
ValueCountFrequency (%)
https://ibb.co/jxbrsq1 24
24.0%
https://ibb.co/gtyz7dq 4
 
4.0%
https://ibb.co/bk79xby 2
 
2.0%
https://ibb.co/0f1xnj8 2
 
2.0%
https://ibb.co/qk6z7mw 2
 
2.0%
https://ibb.co/ngttbxg 2
 
2.0%
https://ibb.co/bw78mjm 2
 
2.0%
https://ibb.co/k0mhqlk 2
 
2.0%
https://ibb.co/nm42mtb 1
 
1.0%
https://ibb.co/hfnhcw3 1
 
1.0%
Other values (58) 58
58.0%
2025-01-27T15:42:36.705790image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 300
13.6%
b 241
 
11.0%
t 215
 
9.8%
s 134
 
6.1%
h 111
 
5.0%
p 105
 
4.8%
c 104
 
4.7%
: 100
 
4.5%
i 100
 
4.5%
. 100
 
4.5%
Other values (46) 690
31.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2200
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 300
13.6%
b 241
 
11.0%
t 215
 
9.8%
s 134
 
6.1%
h 111
 
5.0%
p 105
 
4.8%
c 104
 
4.7%
: 100
 
4.5%
i 100
 
4.5%
. 100
 
4.5%
Other values (46) 690
31.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2200
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 300
13.6%
b 241
 
11.0%
t 215
 
9.8%
s 134
 
6.1%
h 111
 
5.0%
p 105
 
4.8%
c 104
 
4.7%
: 100
 
4.5%
i 100
 
4.5%
. 100
 
4.5%
Other values (46) 690
31.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2200
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 300
13.6%
b 241
 
11.0%
t 215
 
9.8%
s 134
 
6.1%
h 111
 
5.0%
p 105
 
4.8%
c 104
 
4.7%
: 100
 
4.5%
i 100
 
4.5%
. 100
 
4.5%
Other values (46) 690
31.4%
Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:37.214564image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.13
Min length3

Characters and Unicode

Total characters713
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)61.0%

Sample

1st rowPayPal
2nd rowUnionPay
3rd rowSofort
4th rowRakuten Pay
5th rowPaytm
ValueCountFrequency (%)
paypal 21
 
16.5%
pay 17
 
13.4%
apple 7
 
5.5%
google 5
 
3.9%
revolut 4
 
3.1%
wallet 2
 
1.6%
twint 2
 
1.6%
bank 2
 
1.6%
naver 1
 
0.8%
n26 1
 
0.8%
Other values (65) 65
51.2%
2025-01-27T15:42:38.312058image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 105
14.7%
P 74
 
10.4%
y 54
 
7.6%
l 53
 
7.4%
e 45
 
6.3%
o 42
 
5.9%
28
 
3.9%
n 25
 
3.5%
t 25
 
3.5%
i 24
 
3.4%
Other values (43) 238
33.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 713
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 105
14.7%
P 74
 
10.4%
y 54
 
7.6%
l 53
 
7.4%
e 45
 
6.3%
o 42
 
5.9%
28
 
3.9%
n 25
 
3.5%
t 25
 
3.5%
i 24
 
3.4%
Other values (43) 238
33.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 713
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 105
14.7%
P 74
 
10.4%
y 54
 
7.6%
l 53
 
7.4%
e 45
 
6.3%
o 42
 
5.9%
28
 
3.9%
n 25
 
3.5%
t 25
 
3.5%
i 24
 
3.4%
Other values (43) 238
33.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 713
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 105
14.7%
P 74
 
10.4%
y 54
 
7.6%
l 53
 
7.4%
e 45
 
6.3%
o 42
 
5.9%
28
 
3.9%
n 25
 
3.5%
t 25
 
3.5%
i 24
 
3.4%
Other values (43) 238
33.4%
Distinct66
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:38.954411image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length40
Median length18
Mean length12.05
Min length6

Characters and Unicode

Total characters1205
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)60.0%

Sample

1st rowpaypal.com
2nd rowunionpayintl.com
3rd rowsofort.com
4th rowrakuten.com
5th rowpaytm.com
ValueCountFrequency (%)
paypal.com 21
 
21.0%
apple.com/apple-pay 7
 
7.0%
revolut.com 4
 
4.0%
pay.google.com 4
 
4.0%
wallet.google/intl 2
 
2.0%
twint.ch 2
 
2.0%
ininal.com 1
 
1.0%
noon.com 1
 
1.0%
n26.com 1
 
1.0%
uala.com 1
 
1.0%
Other values (56) 56
56.0%
2025-01-27T15:42:39.812849image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 138
11.5%
o 126
10.5%
. 119
 
9.9%
p 106
 
8.8%
c 97
 
8.0%
m 95
 
7.9%
l 65
 
5.4%
e 60
 
5.0%
y 54
 
4.5%
n 42
 
3.5%
Other values (20) 303
25.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1205
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 138
11.5%
o 126
10.5%
. 119
 
9.9%
p 106
 
8.8%
c 97
 
8.0%
m 95
 
7.9%
l 65
 
5.4%
e 60
 
5.0%
y 54
 
4.5%
n 42
 
3.5%
Other values (20) 303
25.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1205
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 138
11.5%
o 126
10.5%
. 119
 
9.9%
p 106
 
8.8%
c 97
 
8.0%
m 95
 
7.9%
l 65
 
5.4%
e 60
 
5.0%
y 54
 
4.5%
n 42
 
3.5%
Other values (20) 303
25.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1205
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 138
11.5%
o 126
10.5%
. 119
 
9.9%
p 106
 
8.8%
c 97
 
8.0%
m 95
 
7.9%
l 65
 
5.4%
e 60
 
5.0%
y 54
 
4.5%
n 42
 
3.5%
Other values (20) 303
25.1%
Distinct66
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:40.207048image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length128
Median length93
Mean length53.21
Min length31

Characters and Unicode

Total characters5321
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)60.0%

Sample

1st rowhttps://www.cnet.com/reviews/paypal-review/
2nd rowhttps://www.trustpilot.com/review/unionpayintl.com
3rd rowhttps://www.trustpilot.com/review/sofort.com
4th rowhttps://www.trustpilot.com/review/www.rakuten.com
5th rowhttps://www.trustradius.com/products/paytm/reviews
ValueCountFrequency (%)
https://www.cnet.com/reviews/paypal-review 21
 
21.0%
https://www.pcmag.com/reviews/apple-pay 7
 
7.0%
https://www.trustpilot.com/review/www.revolut.com 4
 
4.0%
https://www.pcmag.com/reviews/google-pay 4
 
4.0%
https://play.google.com/store/apps/details?id=com.google.android.apps.walletnfcrel&hl=en_in 2
 
2.0%
https://www.trustpilot.com/review/www.twint.ch 2
 
2.0%
https://www.trustpilot.com/review/www.ininal.com 1
 
1.0%
https://au.trustpilot.com/review/noon.com?page=73 1
 
1.0%
https://www.trustpilot.com/review/n26.com 1
 
1.0%
https://www.trustpilot.com/review/uala.com.ar 1
 
1.0%
Other values (56) 56
56.0%
2025-01-27T15:42:40.962076image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 465
 
8.7%
t 447
 
8.4%
w 398
 
7.5%
e 386
 
7.3%
p 303
 
5.7%
o 297
 
5.6%
s 282
 
5.3%
. 272
 
5.1%
a 247
 
4.6%
i 233
 
4.4%
Other values (52) 1991
37.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5321
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 465
 
8.7%
t 447
 
8.4%
w 398
 
7.5%
e 386
 
7.3%
p 303
 
5.7%
o 297
 
5.6%
s 282
 
5.3%
. 272
 
5.1%
a 247
 
4.6%
i 233
 
4.4%
Other values (52) 1991
37.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5321
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 465
 
8.7%
t 447
 
8.4%
w 398
 
7.5%
e 386
 
7.3%
p 303
 
5.7%
o 297
 
5.6%
s 282
 
5.3%
. 272
 
5.1%
a 247
 
4.6%
i 233
 
4.4%
Other values (52) 1991
37.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5321
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 465
 
8.7%
t 447
 
8.4%
w 398
 
7.5%
e 386
 
7.3%
p 303
 
5.7%
o 297
 
5.6%
s 282
 
5.3%
. 272
 
5.1%
a 247
 
4.6%
i 233
 
4.4%
Other values (52) 1991
37.4%
Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2025-01-27T15:42:41.430298image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2200
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)62.0%

Sample

1st rowhttps://ibb.co/JxbrsQ1
2nd rowhttps://ibb.co/s1VmBC7
3rd rowhttps://ibb.co/pWKHfvh
4th rowhttps://ibb.co/whfG4z9
5th rowhttps://ibb.co/rmv6qP7
ValueCountFrequency (%)
https://ibb.co/jxbrsq1 21
 
21.0%
https://ibb.co/gtyz7dq 7
 
7.0%
https://ibb.co/w69nf7j 4
 
4.0%
https://ibb.co/bk79xby 4
 
4.0%
https://ibb.co/5rhx5jd 2
 
2.0%
https://ibb.co/dwmpfbm 1
 
1.0%
https://ibb.co/rdmbbrg 1
 
1.0%
https://ibb.co/mvlcwgs 1
 
1.0%
https://ibb.co/n7n5kkx 1
 
1.0%
https://ibb.co/mbsmsgs 1
 
1.0%
Other values (57) 57
57.0%
2025-01-27T15:42:42.295530image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 300
13.6%
b 236
 
10.7%
t 208
 
9.5%
s 132
 
6.0%
h 111
 
5.0%
p 108
 
4.9%
c 103
 
4.7%
. 100
 
4.5%
o 100
 
4.5%
i 100
 
4.5%
Other values (46) 702
31.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2200
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 300
13.6%
b 236
 
10.7%
t 208
 
9.5%
s 132
 
6.0%
h 111
 
5.0%
p 108
 
4.9%
c 103
 
4.7%
. 100
 
4.5%
o 100
 
4.5%
i 100
 
4.5%
Other values (46) 702
31.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2200
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 300
13.6%
b 236
 
10.7%
t 208
 
9.5%
s 132
 
6.0%
h 111
 
5.0%
p 108
 
4.9%
c 103
 
4.7%
. 100
 
4.5%
o 100
 
4.5%
i 100
 
4.5%
Other values (46) 702
31.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2200
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 300
13.6%
b 236
 
10.7%
t 208
 
9.5%
s 132
 
6.0%
h 111
 
5.0%
p 108
 
4.9%
c 103
 
4.7%
. 100
 
4.5%
o 100
 
4.5%
i 100
 
4.5%
Other values (46) 702
31.9%

Missing values

2025-01-27T15:42:23.617397image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.
2025-01-27T15:42:24.206146image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

CountryApp NameMarket ShareApp Website LinkApp Review LinkApp Screenshot LinkAlternate1 NameAlternate1 WebsiteAlternate1 ReviewAlternate1 ScreenshotAlternate2 NameAlternate2 WebsiteAlternate2 ReviewAlternate2 Screenshot
0United StatesApple Pay43%apple.com/apple-payhttps://www.pcmag.com/reviews/apple-payhttps://ibb.co/gTyz7dQGoogle Paypay.google.comhttps://www.pcmag.com/reviews/google-payhttps://ibb.co/bK79xbyPayPalpaypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1
1ChinaAlipay55%alipay.comhttps://www.rapyd.net/blog/what-is-alipay/https://ibb.co/ysHqJN4WeChat Payweixin.qq.comhttps://www.weareplanet.com/blog/wechat-payhttps://ibb.co/Qk6Z7mwUnionPayunionpayintl.comhttps://www.trustpilot.com/review/unionpayintl.comhttps://ibb.co/s1VmBC7
2GermanyPayPal32%paypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1Klarnaklarna.comhttps://www.trustpilot.com/review/klarna.comhttps://ibb.co/0F1XnJ8Sofortsofort.comhttps://www.trustpilot.com/review/sofort.comhttps://ibb.co/pWKHfvh
3JapanPayPay31%paypay.ne.jphttps://www.g2.com/products/paypay/reviewshttps://ibb.co/v1XgpvsLINE Paypay.line.mehttps://www.trustpilot.com/review/linepay.funhttps://ibb.co/hW2py4PRakuten Payrakuten.comhttps://www.trustpilot.com/review/www.rakuten.comhttps://ibb.co/whfG4z9
4IndiaPhonePe47%phonepe.comhttps://www.trustpilot.com/review/phonepe.comhttps://ibb.co/YfdMZjPGoogle Paypay.google.comhttps://www.pcmag.com/reviews/google-payhttps://ibb.co/bK79xbyPaytmpaytm.comhttps://www.trustradius.com/products/paytm/reviewshttps://ibb.co/rmv6qP7
5United KingdomPayPal29%paypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1Apple Payapple.com/apple-payhttps://www.pcmag.com/reviews/apple-payhttps://ibb.co/gTyz7dQRevolutrevolut.comhttps://www.trustpilot.com/review/www.revolut.comhttps://ibb.co/w69Nf7j
6FrancePaylib24%paylib.frhttps://www.capterra.in/software/209162/paylibhttps://ibb.co/y5vd2g2Lydialydia-app.comhttps://www.trustpilot.com/review/sumeria.eu?page=8https://ibb.co/ZmKrjsdGoogle Paypay.google.comhttps://www.pcmag.com/reviews/google-payhttps://ibb.co/bK79xby
7ItalySatispay20%satispay.comhttps://www.capterra.com/p/180716/Satispay/https://ibb.co/5TRdXzxNexinexi.ithttps://www.trustpilot.com/review/www.nexi.ithttps://ibb.co/hfv5mB7PayPalpaypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1
8CanadaInterac35%interac.cahttps://ca.trustpilot.com/review/interac.cahttps://ibb.co/WHXg50mApple Payapple.com/apple-payhttps://www.pcmag.com/reviews/apple-payhttps://ibb.co/gTyz7dQGoogle Paypay.google.comhttps://www.pcmag.com/reviews/google-payhttps://ibb.co/bK79xby
9BrazilPIX60%mercadopago.com.brhttps://www.trustpilot.com/review/www.mercadopago.com.brhttps://ibb.co/TKGxSkPMercado Pagomercadopago.comhttps://www.capterra.com/p/250909/Mercado-Pago/reviews/https://ibb.co/ngttbxgPayPalpaypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1
CountryApp NameMarket ShareApp Website LinkApp Review LinkApp Screenshot LinkAlternate1 NameAlternate1 WebsiteAlternate1 ReviewAlternate1 ScreenshotAlternate2 NameAlternate2 WebsiteAlternate2 ReviewAlternate2 Screenshot
90UgandaMTN Mobile Money25%momo.mtn.comhttps://pctechmag.com/2020/05/mtn-momo-app-review/https://ibb.co/XC141GYAirtel Ugandaairtel.co.ughttps://tech-ish.com/2021/02/01/new-m-pesa-app-really-good/https://ibb.co/vZxkyDRPayPalpaypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1
91MacauMacau Pass15%macaupass.comhttps://play.google.com/store/apps/details/MPay?id=com.macaupass.rechargeEasy&hl=en-UShttps://ibb.co/syhwnmxAlipayalipay.comhttps://www.rapyd.net/blog/what-is-alipay/https://ibb.co/ysHqJN4WeChat Paypay.wechat.comhttps://www.tripadvisor.in/ShowTopic-g294211-i642-k14971097-WeChat_Pay_enables_digital_payment_of_8_foreign_e_wallets-China.htmlhttps://ibb.co/G5fM7vQ
92CameroonOrange Money15%orange.comhttps://africanreview.com/finance/banking-a-finance/orange-money-fintech-is-proving-a-game-changer-in-africahttps://ibb.co/0MptPcgMTN Mobile Moneymomo.mtn.comhttps://pctechmag.com/2020/05/mtn-momo-app-review/https://ibb.co/3WqkHHtPayPalpaypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1
93JordanZain Cash10%zaincash.iqhttps://www.appbrain.com/app/zaincash-%D8%B2%D9%8A%D9%86-%D9%83%D8%A7%D8%B4/mobi.foo.zaincashhttps://ibb.co/vkKXkkDReflectpal.reflectapp.comhttps://play.google.com/store/apps/details?id=com.arabbank.neobank&hl=en-UShttps://ibb.co/v4gDFyYAnyPayanypay.co.thhttps://www.scam-detector.com/validator/anypay-io-review/https://ibb.co/rvjmcdJ
94TunisiaE-dinar20%https://play.google.com/store/apps/details?id=com.kaoun.flouci&hl=enRead 4 Flouci Reviews (2025) | flouci.com reviewshttps://ibb.co/q1hPhBgPayPalpaypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1Twinttwint.chhttps://www.trustpilot.com/review/www.twint.chhttps://ibb.co/py5DyNY
95CambodiaPi Pay15%pipay.comhttps://appshunter.io/ios/app/1234143591https://ibb.co/vzLpkwgABA Mobileababank.comhttps://play.google.com/store/apps/details?id=com.paygo24.ibank&hl=en_INhttps://ibb.co/3W34yQWWing Bankwingbank.com.khhttps://appshunter.io/ios/app/1113286385https://ibb.co/GQbMYht
96BoliviaTigo Money15%tigomoney.comhttps://tigo-money-bolivia.en.softonic.com/androidhttps://ibb.co/XY5CKXHPagoEfectivopagoefectivo.pehttps://www.linkedin.com/pulse/pagoefectivo-transforming-cash-payments-peruvian-tony-cueva-bravo-ae8kehttps://ibb.co/jJZj29hPayPalpaypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1
97BahrainBenefit Pay20%benefit.bhhttps://download.cnet.com/benefitpay/3000-2057_4-78509523.htmlhttps://ibb.co/wBrjY3cPayPalpaypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1Taptap.companyhttps://www.trustpilot.com/review/tap.companyhttps://ibb.co/fqT1scD
98LatviaMobilly15%swedbank.comhttps://appshunter.io/ios/app/344161302https://ibb.co/n8tBqxRPayPalpaypal.comhttps://www.cnet.com/reviews/paypal-review/https://ibb.co/JxbrsQ1Google walletwallet.google/intl/https://play.google.com/store/apps/details?id=com.google.android.apps.walletnfcrel&hl=en_INhttps://ibb.co/5rHX5jD
99ParaguayTigo Money15%Tigo Moneyhttps://tigo-money-bolivia.en.softonic.com/androidhttps://ibb.co/z2YF9B1Personal Paypersonalpay.comhttps://play.google.com/store/apps/details?id=ar.com.personalpay&hl=en_INhttps://ibb.co/0KZD4tkVisavisa.comhttps://www.trustpilot.com/review/visa.comhttps://ibb.co/RSSHY9w